AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (7.6 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Article | Open Access

Aging-related alternative splicing landscapes across human T cells

Lipeng Mao1,2,§Yue Zhu1,2,§Bei Zhang1,2,§Guangjie Wu3,§Qiuyue Feng1,2Oscar Junhong Luo1,2( )
Department of Systems Biomedical Sciences, School of Medicine, Jinan University, Guangzhou 510630, China
Guangdong-Hong Kong-Macau Great Bay Area Geroscience Joint Laboratory, School of Medicine, Jinan University, Guangzhou 510630, China
Department of Microbiology and Immunology, Institute of Geriatric Immunology, School of Medicine, Jinan University, Guangzhou 510630, China

§ These authors contributed equally to this work.

Show Author Information

Abstract

As age-related diseases escalate, deciphering molecular mechanism of immune aging is vital. T cells, crucial in adaptive immunity, undergo aging-related transformations in quantity and quality. The interconnection between aging and alternative splicing of gene expression in different T cell subtype is still unclear. Thus, we examined age-related gene alternative splicing in numerous immune cell subgroups, constructing an aging-associated atlas for alternative splicing across human T cell subtypes. Our study identified numerous age-related alternative splicing events in genes linked to T cell activation, differentiation, migration, and apoptosis. Genes like PDCD4 and ARCN1 with age group-specific alternative splicing events and implicated in T cell aging hint at potential therapeutic targets for immune aging. Overall, our findings present a comprehensive alternative splicing atlas for healthy aging-related molecular programs, introducing fresh perspectives for T cell transformation regulation during aging, and inspiring new approaches for novel T cell aging intervention molecules and methods.

Electronic Supplementary Material

Download File(s)
AgingRes-2023-0007_ESM.pdf (1.6 MB)

References

[1]
Wang, C., Lutes, L. K., Barnoud, C., Scheiermann, C. The circadian immune system. Science Immunology, 2022, 7: eabm2465. https://doi.org/10.1126/sciimmunol.abm2465
[2]
Ponnappan, S., Ponnappan, U. Aging and immune function: Molecular mechanisms to interventions. Antioxidants & Redox Signaling, 2011, 14: 1551–1585. https://doi.org/10.1089/ars.2010.3228
[3]
Dong, C. Cytokine regulation and function in T cells. Annual Review of Immunology, 2021, 39: 51–76. https://doi.org/10.1146/annurev-immunol-061020-053702
[4]
Brummelman, J., Pilipow, K., Lugli, E. The single-cell phenotypic identity of human CD8(+) and CD4(+) T cells. International Review of Cell and Molecular Biology, 2018, 341: 63–124. https://doi.org/10.1016/bs.ircmb.2018.05.007
[5]
Goronzy, J. J. Weyand, C. M. Successful and maladaptive T cell aging. Immunity, 2017, 46: 364–378. https://doi.org/10.1016/j.immuni.2017.03.010
[6]
Aiello, A., Farzaneh, F., Candore, G., Caruso, C., Davinelli, S., Gambino, C. M., Ligotti, M. E., Zareian, N., Accardi, G. Immunosenescence and its hallmarks: How to oppose aging strategically? A review of potential options for therapeutic intervention. Frontiers in Immunology, 2019, 10: 2247. https://doi.org/10.3389/fimmu.2019.02247
[7]
Lian, J. Y., Yue, Y., Yu, W. N., Zhang, Y. Immunosenescence: A key player in cancer development. Journal of Hematology & Oncology, 2020, 13: 151. https://doi.org/10.1186/s13045-020-00986-z
[8]
Baralle, F. E., Giudice, J. Alternative splicing as a regulator of development and tissue identity. Nature Reviews Molecular Cell Biology, 2017, 18: 437–451. https://doi.org/10.1038/nrm.2017.27
[9]
Chao, Y., Jiang, Y., Zhong, M., Wei, K., Hu, C., Qin, Y., Zuo, Y., Yang, L., Shen, Z., Zou, C. Regulatory roles and mechanisms of alternative RNA splicing in adipogenesis and human metabolic health. Cell & Bioscience, 2021, 11: 66. https://doi.org/10.1186/s13578-021-00581-w
[10]
Wang, Y., Liu, J., Huang, B. O., Xu, Y. M., Li, J., Huang, L. F., Lin, J., Zhang, J., Min, Q. H., Yang, W. M. et al. Mechanism of alternative splicing and its regulation. Biomedical Reports, 2015, 3: 152–158. https://doi.org/10.3892/br.2014.407
[11]
Yabas, M., Elliott, H., Hoyne, G. F. The role of alternative splicing in the control of immune homeostasis and cellular differentiation. International Journal of Molecular Sciences, 2015, 17: 3. https://doi.org/10.3390/ijms17010003
[12]
Giles, J. R., Manne, S., Freilich, E., Oldridge, D. A., Baxter, A. E., George, S., Chen, Z., Huang, H., Chilukuri, L., Carberry, M. et al. Human epigenetic and transcriptional T cell differentiation atlas for identifying functional T cell-specific enhancers. Immunity, 2022, 55: 557–574.e7. https://doi.org/10.1016/j.immuni.2022.02.004
[13]
Mahnke, Y. D., Brodie, T. M., Sallusto, F., Roederer, M., Lugli, E. The who’s who of T-cell differentiation: Human memory T-cell subsets. European Journal of Immunology, 2013, 43: 2797–2809. https://doi.org/10.1002/eji.201343751
[14]
Henning, A. N., Klebanoff, C. A., Restifo, N. P. Silencing stemness in T cell differentiation. Science, 2018, 359: 163–164. https://doi.org/10.1126/science.aar5541
[15]
Shen, S., Park, J. W., Lu, Z. X., Lin, L., Henry, M. D., Wu, Y. N., Zhou, Q., Xing, Y. rMATS: Robust and flexible detection of differential alternative splicing from replicate RNA-Seq data. Nucleic Acids Research, 2014, 111: E5593–E5601. https://doi.org/10.1073/pnas.1419161111
[16]
Zhu, J. F., Yamane, H., Paul, W. E. Differentiation of effector CD4 T cell populations. Annual Review of Immunology, 2010, 28: 445–489. https://doi.org/10.1146/annurev-immunol-030409-101212
[17]
Pennock, N. D., White, J. T., Cross, E. W., Cheney, E. E., Tamburini, B. A., Kedl, R. M. T cell responses: Naive to memory and everything in between. Advances in Physiology Education, 2013, 37: 273–283. https://doi.org/10.1152/advan.00066.2013
[18]
Caccamo, N., Joosten, S. A., Ottenhoff, T. H. M., Dieli, F. Atypical human effector/memory CD4(+) T cells with a naive-like phenotype. Frontiers in Immunology, 2018, 9: 2832. https://doi.org/10.3389/fimmu.2018.02832
[19]
Bacchetta, R., Gregori, S., Roncarolo, M. G. CD4+ regulatory T cells: Mechanisms of induction and effector function. Autoimmunity Reviews, 2005, 4: 491–496. https://doi.org/10.1016/j.autrev.2005.04.005
[20]
Rocamora-Reverte, L., Melzer, F. L., Würzner, R., Weinberger, B. The complex role of regulatory T cells in immunity and aging. Frontiers in Immunology, 2021, 11: 616949. https://doi.org/10.3389/fimmu.2020.616949
[21]
Izumi, K., Brett, M., Nishi, E., Drunat, S., Tan, E. S., Fujiki, K., Lebon, S., Cham, B., Masuda, K., Arakawa, M. et al. ARCN1 mutations cause a recognizable craniofacial syndrome due to COPI-mediated transport defects. Journal of Inherited Metabolic Disease, 2016, 99: 451–459. https://doi.org/10.1016/j.ajhg.2016.06.011
[22]
Gattinoni, L., Speiser, D. E., Lichterfeld, M., Bonini, C. T memory stem cells in health and disease. Nature Medicine, 2017, 23: 18–27. https://doi.org/10.1038/nm.4241
[23]
Kohli, K., Pillarisetty, V. G., Kim, T. S. Key chemokines direct migration of immune cells in solid tumors. Cancer Gene Therapy, 2022, 29: 10–21. https://doi.org/10.1038/s41417-021-00303-x
[24]
Li, M. D., Yao, D. L., Zeng, X. B., Kasakovski, D., Zhang, Y. K., Chen, S. H., Zha, X. F., Li, Y. Q., Xu, L. Age related human T cell subset evolution and senescence. Immunity & Ageing, 2019, 16: 24. https://doi.org/10.1186/s12979-019-0165-8
[25]
Goronzy, J. J., Weyand, C. M. Mechanisms underlying T cell ageing. Nature Reviews Immunology, 2019, 19: 573–583. https://doi.org/10.1038/s41577-019-0180-1
[26]
Weinelt, N., van Wijk, S. J. L. Ubiquitin-dependent and-independent functions of OTULIN in cell fate control and beyond. Cell Death and Differentiation, 2021, 28: 493–504. https://doi.org/10.1038/s41418-020-00675-x
[27]
Colpitts, S. L., Dalton N. M., Phillip, S. IL-7 receptor expression provides the potential for long-term survival of both CD62Lhigh central memory T cells and Th1 effector cells during Leishmania major infection. Journal of Immunology, 2009, 182: 5702–5711. https://doi.org/10.4049/jimmunol.0803450
[28]
Wang, Q., Yang, H. S. The role of Pdcd4 in tumour suppression and protein translation. Biology of the Cell, 2018, 110: 169–177. https://doi.org/10.1111/boc.201800014
[29]
Nolz, J. C., Starbeck-Miller, G. R., Harty, J. T. Naive, effector and memory CD8 T-cell trafficking: Parallels and distinctions. Immunotherapy, 2011, 3: 1223–1233. https://doi.org/10.2217/imt.11.100
[30]
Kaech, S. M., Wherry, E. J., Ahmed, R. Effector and memory T-cell differentiation: Implications for vaccine development. Nature Reviews Immunology, 2002, 2: 251–262. https://doi.org/10.1038/nri778
[31]
Jiang, W. Q., He, Y. J., He, W. G., Wu, G. S., Zhou, X. L., Sheng, Q. S., Zhong, W. X., Lu, Y. M., Ding, Y. F., Lu, Q., et al. Exhausted CD8+T cells in the tumor immune microenvironment: new pathways to therapy. Frontiers in Immunology, 2021, 11: 622509. https://doi.org/10.3389/fimmu.2020.622509
[32]
Matrone, C., Petrillo, F., Nasso, R., Ferretti, G. Fyn tyrosine kinase as harmonizing factor in neuronal functions and dysfunctions. International Journal of Molecular Sciences, 2020, 21: E4444. https://doi.org/10.3390/ijms21124444
[33]
Stanton, T., Boxall, S., Hirai, K., Dawes, R., Tonks, S., Yasui, T., Kanaoka, Y., Yuldasheva, N., Ishiko, O., Bodmer, W. et al. A high-frequency polymorphism in exon 6 of the CD45 tyrosine phosphatase gene (PTPRC) resulting in altered isoform expression. Proceedings of the National Academy of Sciences of the United States of America, 2003, 100: 5997–6002. https://doi.org/10.1073/pnas.0931490100
[34]

Jun, D. Y., Kim, H., Jang, W. Y., Lee, J. Y., Fukui, K., Kim, Y. H. Ectopic overexpression of LAPTM5 results in lysosomal targeting and induces Mcl-1 down-regulation, Bak activation, and mitochondria-dependent apoptosis in human HeLa cells. PLoS One, 2017, 12: e0176544.

[35]
Zhang, H. M., Weyand, C. M., Goronzy, J. J. Hallmarks of the aging T-cell system. The FEBS Journal, 2021, 288: 7123–7142. https://doi.org/10.1111/febs.15770
[36]
Bhadra, M., Howell, P., Dutta, S., Heintz, C., Mair, W. B. Alternative splicing in aging and longevity. Human Genetics, 2020, 139: 357–369. https://doi.org/10.1007/s00439-019-02094-6
[37]

Salam, N., Rane, S., Das, R., Faulkner, M., Gund, R., Kandpal, U., Lewis, V., Mattoo, H., Prabhu, S., Ranganathan, V. et al. T cell ageing: Effects of age on development, survival & function. The Indian Journal of Medical Research, 2013, 138: 595–608.

[38]
Sun, X. P., Nguyen, T., Achour, A., Ko, A., Cifello, J., Ling, C., Sharma, J., Hiroi, T., Zhang, Y. Q., Chia, C. W., et al. Longitudinal analysis reveals age-related changes in the T cell receptor repertoire of human T cell subsets. The Journal of Clinical Investigation, 2022, 132: e158122. https://doi.org/10.1172/JCI158122
[39]
Jergović, M., Contreras, N. A., Nikolich-Žugich, J. Impact of CMV upon immune aging: Facts and fiction. Medical Microbiology and Immunology, 2019, 208: 263–269. https://doi.org/10.1007/s00430-019-00605-w
[40]
Crooke, S. N., Ovsyannikova, I. G., Poland, G. A., Kennedy, R. B. Immunosenescence: A systems-level overview of immune cell biology and strategies for improving vaccine responses. Experimental Gerontology, 2019, 124: 110632. https://doi.org/10.1016/j.exger.2019.110632
[41]

Janeway, C. A. Jr. The co-receptor function of CD4. Seminars in Immunology,, 1991, 3: 153–160.

[42]
Dawes, R., Petrova, S., Liu, Z., Wraith, D., Beverley, P. C., Tchilian, E. Z. Combinations of CD45 isoforms are crucial for immune function and disease. Journal of Immunology, 2006, 176: 3417–3425. https://doi.org/10.4049/jimmunol.176.6.3417
[43]
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, C., Zaleski, C., Jha, S., Batut, P., Chaisson, M., Gingera, T. R. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics, 2013, 29: 15–21. https://doi.org/10.1093/bioinformatics/bts635
[44]
Wu, T., Hu, E., Xu, S., Chen, M., Guo, P., Dai, Z., Feng, T., Zhou, L., Tang, W., Zhan, L. et al. clusterProfiler 4.0: A universal enrichment tool for interpreting omics data. The Innovation, 2021, 2: 100141. https://doi.org/10.1016/j.xinn.2021.100141
Aging Research
Article number: 9340007
Cite this article:
Mao L, Zhu Y, Zhang B, et al. Aging-related alternative splicing landscapes across human T cells. Aging Research, 2023, 1(1): 9340007. https://doi.org/10.26599/AGR.2023.9340007

2167

Views

341

Downloads

0

Crossref

Altmetrics

Received: 27 March 2023
Revised: 26 April 2023
Accepted: 27 April 2023
Published: 29 May 2023
© The Author(s) 2023. Aging Research published by Tsinghua University Press.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Return